{"id":142469,"date":"2023-08-17T09:03:51","date_gmt":"2023-08-17T09:03:51","guid":{"rendered":"https:\/\/amplify.nabshow.com\/?post_type=articles&#038;p=142469"},"modified":"2024-09-08T00:12:38","modified_gmt":"2024-09-08T00:12:38","slug":"ic-ai-vs-humanity-creativity","status":"publish","type":"articles","link":"https:\/\/jwolfepr.com\/dev\/articles\/ic-ai-vs-humanity-creativity\/","title":{"rendered":"AI and the Future of the Creative Industries"},"content":{"rendered":"\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-flow wp-block-group-is-layout-flow\">\n<div class=\"wp-block-columns article-content is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:100%\">\n<figure class=\"wp-block-image size-large is-resized\"><img data-recalc-dims=\"1\" decoding=\"async\" src=\"https:\/\/i0.wp.com\/jwolfepr.com\/dev\/wp-content\/uploads\/2024\/09\/Treachery-Magritte.jpg?ssl=1\" alt=\"The Treachery of Images, 1929 by Rene Magritte\" class=\"wp-image-94496\" style=\"width:840px;height:auto\"\/><figcaption class=\"wp-element-caption\">\u201cThe Treachery of Images,\u201d 1929, by Rene Magritte<\/figcaption><\/figure>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-flow wp-block-group-is-layout-flow\">\n<hr class=\"wp-block-separator has-text-color has-luminous-vivid-amber-color has-alpha-channel-opacity has-luminous-vivid-amber-background-color has-background\"\/>\n\n\n\n<hr class=\"wp-block-separator has-text-color has-luminous-vivid-amber-color has-alpha-channel-opacity has-luminous-vivid-amber-background-color has-background\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">TL;DR<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><em>Generative AI is experiencing an unprecedented growth trajectory, and is anticipated to expand from $40 billion in today\u2019s marketplace to a staggering $1.3 trillion by 2032.<\/em><\/li>\n\n\n\n<li><em>The rise of generative AI has sparked complex ethical and legal debates, including issues surrounding copyright, intellectual property rights, and data privacy.<\/em><\/li>\n\n\n\n<li><em>With its potential to disrupt traditional creative work, AI&#8217;s role in the creative industries has become a critical point during the Hollywood strikes.<\/em><\/li>\n\n\n\n<li><em>Scholars argue that while generative AI can mimic certain aspects of human creativity, it lacks the ability to produce genuinely novel and unique works.<\/em><\/li>\n\n\n\n<li><em>In the future, generative AI could be embraced as an assistant to augment human creativity, be used to monopolize and commodify human creativity, or place a premium on \u201chuman-made\u201d \u2014 or all three.<\/em><\/li>\n<\/ul>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<hr class=\"wp-block-separator has-text-color has-luminous-vivid-amber-color has-alpha-channel-opacity has-luminous-vivid-amber-background-color has-background\"\/>\n\n\n\n<hr class=\"wp-block-separator has-text-color has-luminous-vivid-amber-color has-alpha-channel-opacity has-luminous-vivid-amber-background-color has-background\"\/>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<\/div><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">READ MORE: <a href=\"https:\/\/www.sciencefocus.com\/future-technology\/ai-art-creativity-war\" target=\"_blank\" rel=\"noreferrer noopener\">Why AI will ultimately lose the war of creativity with humanity (BBC)<\/a><\/h3>\n\n\n\n<p>In the age of artificial intelligence, the concept of creativity has become a fascinating battleground. The Hollywood strikes have thrown the debate into sharp relief, pitting guild members against major studios seeking to disrupt a successful century-old business model by adopting Silicon Valley\u2019s \u201cmove fast and break things\u201d ethos.<\/p>\n\n\n\n<p><a href=\"https:\/\/www.wired.com\/story\/hollywoods-future-belongs-to-people-not-machines\/\" target=\"_blank\" rel=\"noreferrer noopener\">Madeline Ashby at <em>Wired<\/em><\/a> deftly outlines the stakes for the striking writers and actors. \u201cCultural production\u2019s current landscape, the one the Hollywood unions are bargaining for a piece of, was transformed forever 10 years ago when Netflix released <em>House of Cards<\/em>. Now, in 2023, those same unions are bracing for the potential impacts of generative AI,\u201d she writes.<\/p>\n\n\n\n<p>\u201cAs negotiations between Hollywood studios and SAG heated up in July, the use of AI in filmmaking became one of the most divisive issues. One SAG member told <a href=\"https:\/\/deadline.com\/2023\/07\/actors-strike-ai-kim-kardashian-fran-drescher-contract-deadline-1235432142\/\" target=\"_blank\" rel=\"noreferrer noopener\"><em>Deadline<\/em><\/a> \u2018actors see <em>Black Mirror<\/em>\u2019s \u201cJoan Is Awful\u201d as a documentary of the future, with their likenesses sold off and used any way producers and studios want.\u2019 <\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img data-recalc-dims=\"1\" decoding=\"async\" src=\"https:\/\/i0.wp.com\/jwolfepr.com\/dev\/wp-content\/uploads\/2024\/09\/BlackMirror-JoanisAwful.gif?ssl=1\" alt=\"From the \u201cJoan is Awful\u201d episode of \u201cBlack Mirror,\u201d Cr: Netflix\" class=\"wp-image-140147\"\/><figcaption class=\"wp-element-caption\">From the \u201cJoan is Awful\u201d episode of \u201cBlack Mirror,\u201d Cr: Netflix<\/figcaption><\/figure>\n\n\n\n<p>\u201cThe Writers Guild of America is striking in hopes of receiving residuals based on views from Netflix and other streamers \u2014 just like they\u2019d get if their broadcast or cable show lived on in syndication. In the meantime, they worry studios will replace them with the same chatbots that fanfic writers have <a href=\"https:\/\/www.wired.com\/story\/fanfiction-omegaverse-sex-trope-artificial-intelligence-knotting\/\" target=\"_blank\" rel=\"noreferrer noopener\">caught reading up on their sex tropes<\/a>.\u201d<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">READ MORE: <a href=\"https:\/\/www.wired.com\/story\/hollywoods-future-belongs-to-people-not-machines\/\" target=\"_blank\" rel=\"noreferrer noopener\">Hollywood\u2019s Future Belongs to People\u2014Not Machines (Wired)<\/a><\/h3>\n\n\n\n<p>AI researcher Ahmed Elgammal, a professor at the Department of Computer Science at Rutgers University, where he leads the Art and Artificial Intelligence Laboratory, recently sat down with host <a href=\"https:\/\/www.sciencefocus.com\/future-technology\/ai-art-creativity-war\" target=\"_blank\" rel=\"noreferrer noopener\">Alex Hughes<\/a> on the BBC Science Focus <em>Instant Genuis<\/em> podcast to discuss the limits of AI against human creativity.<\/p>\n\n\n\n<p>In the episode \u201c<a href=\"https:\/\/www.sciencefocus.com\/future-technology\/podcast-ai-art\" target=\"_blank\" rel=\"noreferrer noopener\">AI\u2019s fight to understand creativity<\/a>,\u201d which you can listen to in the audio player below, Elgammal explores the capabilities and limitations of AI in generating images, the ethical dilemmas surrounding copyright, and the profound distinction between AI-generated images and human-created art. This conversation sheds light on the complex relationship between machine learning and the uniquely human quality of creativity, setting the stage for the ongoing debate at the intersection of art and technology.<\/p>\n\n\n\n<p>\u201cThe current generation of AI is limited to copying the work of humans. It must be controlled largely by people to create something useful. It\u2019s a great tool but not something that can be creative itself,\u201d the AI art pioneer tells Hughes.<\/p>\n\n\n\n<p>\u201cWe must be conscious about what\u2019s happening in the world and have an opinion to create real art. The AIs simply don\u2019t have this.\u201d<\/p>\n\n\n\n<iframe style=\"border-radius:12px\" src=\"https:\/\/open.spotify.com\/embed\/episode\/0jRGzeNrq298jy3gyfHxM7?utm_source=generator\" width=\"100%\" height=\"352\" frameBorder=\"0\" allowfullscreen=\"\" allow=\"autoplay; clipboard-write; encrypted-media; fullscreen; picture-in-picture\" loading=\"lazy\"><\/iframe>\n\n\n\n<h2 class=\"wp-block-heading\">The Growth and Impact of Generative AI<\/h2>\n\n\n\n<p>Generative AI is experiencing an unprecedented growth trajectory, with Bloomberg Intelligence forecasting its expansion from $40 billion in today\u2019s marketplace to a staggering $1.3 trillion by 2032.<\/p>\n\n\n\n<p>Bloomberg\u2019s latest report, \u201c<a href=\"https:\/\/www.bloomberg.com\/company\/press\/generative-ai-to-become-a-1-3-trillion-market-by-2032-research-finds\/\" target=\"_blank\" rel=\"noreferrer noopener\">2023 Generative AI Growth<\/a>,\u201d demonstrates that this growth is not confined to mere numbers, but represents a fundamental shift in the way industries operate.<\/p>\n\n\n\n<p>\u201cThe world is poised to see an explosion of growth in the generative AI sector over the next 10 years that promises to fundamentally change the way the technology sector operates,\u201d Mandeep Singh, senior technology analyst at Bloomberg Intelligence and lead author of the report, emphasizes. \u201cThe technology is set to become an increasingly essential part of IT spending, ad spending, and cybersecurity as it develops.\u201d<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img data-recalc-dims=\"1\" decoding=\"async\" src=\"https:\/\/i0.wp.com\/jwolfepr.com\/dev\/wp-content\/uploads\/2024\/09\/Bloomberg_Chart.jpg?ssl=1\" alt=\"Generative AI is poised to expand its impact from less than 1% of total IT hardware, software services, ad spending and gaming market spending to 10% by 2032. Cr: Bloomberg Intelligence\" class=\"wp-image-142471\"\/><figcaption class=\"wp-element-caption\">Generative AI is poised to expand its impact from less than 1% of total IT hardware, software services, ad spending and gaming market spending to 10% by 2032. Cr: Bloomberg Intelligence<\/figcaption><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\">READ MORE: <a href=\"https:\/\/www.bloomberg.com\/company\/press\/generative-ai-to-become-a-1-3-trillion-market-by-2032-research-finds\/\" target=\"_blank\" rel=\"noreferrer noopener\">Generative AI to Become a $1.3 Trillion Market by 2032, Research Finds (Bloomberg Intelligence)<\/a><\/h3>\n\n\n\n<p>Reflecting a broader trend in the technological landscape, Bloomberg predicts that generative AI will move revenue distribution away from infrastructure and towards software and services.<\/p>\n\n\n\n<p><a href=\"https:\/\/voicebot.ai\/\" target=\"_blank\" rel=\"noreferrer noopener\">Voicebot.ai<\/a> editor and publisher <a href=\"https:\/\/synthedia.substack.com\/p\/generative-ai-to-reach-13-trillion\" target=\"_blank\" rel=\"noreferrer noopener\">Bret Kinsella analyzes this shift<\/a> on his Synthedia blog. \u201cThe report shows that 85% of the revenue in 2022 was related to computing infrastructure used to train and operate generative AI models,\u201d he writes. \u201cAnother 10% is dedicated to running the models, also known as inference. Generative AI software and \u2018Other\u2019 services (mostly web services) accounted for just 5% of the total market.\u201d<\/p>\n\n\n\n<p>But that revenue distribution will change radically over the next decade, he notes. \u201cIn 2027, researchers estimate infrastructure-related revenue to decline from 95% of the market to just 56%. The figure will be about 49% in 2032.\u201d<\/p>\n\n\n\n<p>As a result, says Kinsella, \u201cgenerative AI training infrastructure will become a $473 billion market while generative AI software [will] reach $280 billion, and the supporting services will surpass $380 billion. This may seem outlandish to forecast a software segment of a few hundred million dollars will transform into a few hundred billion in a decade. However, the impact of generative AI is so far-reaching it makes everyone rethink old assumptions.\u201d<\/p>\n\n\n\n<p>Specialized generative AI assistants and code generation software are emerging as powerful tools, allowing businesses to leverage AI in innovative ways. However, this growth also brings challenges. Kinsella highlights the need for caution, pointing out that the rapid adoption of AI technologies raises questions about accessibility, ethics, and regulation. Balancing innovation with responsible development will be a key consideration as generative AI continues to evolve, requiring new regulations and ethical considerations in areas such as copyright, data privacy, and algorithmic bias.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">READ MORE: <a href=\"https:\/\/synthedia.substack.com\/p\/generative-ai-to-reach-13-trillion\" target=\"_blank\" rel=\"noreferrer noopener\">Generative AI to Reach $1.3 Trillion in Annual Revenue &#8212; Let\u2019s Break That Down (Synthedia)<\/a><\/h3>\n\n\n\n<h2 class=\"wp-block-heading\">Human Creativity Trumps AI<\/h2>\n\n\n\n<p>Creativity is a complex and multifaceted subject, inspiring fierce debate since long before the days of Dada artists such as Marcel Duchamp, who in 1917 displayed a sculpture comprising a porcelain urinal signed \u201cR. Mutt.\u201d Much like pornography, people find art \u2014 and creativity, the driving force behind all art \u2014 difficult to define. \u201cI don\u2019t know much about art, but I know what I like,\u201d the popular saying goes.<\/p>\n\n\n\n<p>Elgammal draws a clear line between AI-generated images and human-created art. \u201cAI doesn\u2019t generate art, AI generates images. Making an image doesn\u2019t make you an artist; it\u2019s the artist behind the scene that makes it art,\u201d he tells Hughes. In other words, human creativity will always trump AI.<\/p>\n\n\n\n<p>AI\u2019s ability to generate realistic images is both impressive and concerning. While the technology has advanced significantly, <a href=\"https:\/\/twitter.com\/joshua_xu_\/status\/1689019874667024384\" target=\"_blank\" rel=\"noreferrer noopener\">now capable of delivering lifelike, photorealistic \u201cAI clones,\u201d<\/a> it is not without flaws. Errors in AI-generated images, such as distorted fingers and hands, and the inability to produce something truly new are both significant limitations.<\/p>\n\n\n\n<p>An article by <a href=\"https:\/\/theconversation.com\/ai-can-replicate-human-creativity-in-two-key-ways-but-falls-apart-when-asked-to-produce-something-truly-new-204437\" target=\"_blank\" rel=\"noreferrer noopener\">Chloe Preece and Hafize \u00c7elik in <em>The Conversation<\/em><\/a> explores AI\u2019s inability to replicate human creativity, arguing that while AI can mimic certain aspects of creativity, it falls short in producing something genuinely novel and unique.<\/p>\n\n\n\n<p>The key characteristic of what they call AI\u2019s creative processes \u201cis that the current computational creativity is systematic, not impulsive, as its human counterpart can often be. It is programmed to process information in a certain way to achieve particular results predictably, albeit in often unexpected ways.\u201d<\/p>\n\n\n\n<p>The duo cites Margaret Boden, a research professor of cognitive science at the University of Sussex in the UK, on the three types of creativity: combinational, exploratory, and transformational.<\/p>\n\n\n\n<p>\u201cCombinational creativity combines familiar ideas together. Exploratory creativity generates new ideas by exploring \u2018structured conceptual spaces,\u2019 that is, tweaking an accepted style of thinking by exploring its contents, boundaries and potential. Both of these types of creativity are not a million miles from generative AI\u2019s algorithmic production of art; creating novel works in the same style as millions of others in the training data, a \u2018synthetic creativity,\u2019\u201d they write.<\/p>\n\n\n\n<p>\u201cTransformational creativity, however, means generating ideas beyond existing structures and styles to create something entirely original; this is at the heart of current debates around AI in terms of fair use and copyright \u2014 very much uncharted legal waters, so we will have to wait and see what the courts decide.\u201d<\/p>\n\n\n\n<p>But the main flaw Preece and \u00c7elik find with generative AI is its consumer-centric approach. \u201cIn fact, this is perhaps the most significant difference between artists and AI: while artists are self- and product-driven, AI is very much consumer-centric and market-driven \u2014 we only get the art we ask for, which is not perhaps, what we need.\u201d<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">READ MORE: <a href=\"https:\/\/theconversation.com\/ai-can-replicate-human-creativity-in-two-key-ways-but-falls-apart-when-asked-to-produce-something-truly-new-204437\" target=\"_blank\" rel=\"noreferrer noopener\">AI can replicate human creativity in two key ways \u2013 but falls apart when asked to produce something truly new (The Conversation)<\/a><\/h3>\n\n\n\n<h2 class=\"wp-block-heading\">The Three Body Problem: Copyright, Intellectual Property and Ethics<\/h2>\n\n\n\n<p>The rapid evolution and widespread adoption of generative AI has also given rise to a complex web of ethical and legal challenges. As AI systems become more sophisticated in generating content that closely resembles human creativity, questions surrounding copyright, intellectual property rights, data privacy, and algorithmic bias have come to the forefront.<\/p>\n\n\n\n<p>\u201cThis is far more than a philosophical debate about human versus machine intelligence,\u201d technology writer <a href=\"https:\/\/www.nytimes.com\/2023\/07\/15\/technology\/ai-inventor-patents.html\" target=\"_blank\" rel=\"noreferrer noopener\">Steve Lohr notes in <em>The New York Times<\/em><\/a>. \u201cThe role, and legal status, of AI in invention also have implications for the future path of innovation and global competitiveness.\u201d<\/p>\n\n\n\n<p>The <a href=\"https:\/\/artificialinventor.com\/\" target=\"_blank\" rel=\"noreferrer noopener\">Artificial Inventor Project<\/a>, a group of intellectual property lawyers founded by Dr. Ryan Abbott, a professor at the University of Surrey School of Law in England, is pressing patent agencies, courts and policymakers to address these questions, Lohr reports. The project has filed pro bono test cases in the United States and more than a dozen other countries seeking legal protection for AI-generated inventions.<\/p>\n\n\n\n<p>\u201cThis is about getting the incentives right for a new technological era,\u201d Dr. Abbott, who is also a physician and teaches at the David Geffen School of Medicine at UCLA, told Lohr.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">READ MORE: <a href=\"https:\/\/www.nytimes.com\/2023\/07\/15\/technology\/ai-inventor-patents.html\" target=\"_blank\" rel=\"noreferrer noopener\">Can A.I. Invent? (The New York Times)<\/a><\/h3>\n\n\n\n<p>Elgammal spends a considerable amount of time delving into these complex issues. He identifies a three-way copyright problem that has emerged with the current generation of AI image tools. The stakeholders include the innovator, who might inadvertently violate the copyright of other artists; the original artist, whose work might be transformed or mixed without consent; and the AI developer, the company that develops and trains the AI system based on these images.<\/p>\n\n\n\n<p>This is a new and significant problem, and one that current copyright laws are not equipped to handle. The situation is further complicated by the fact that the latest models are trained on billions of images, often without proper consent, leading to a messy situation where copyright infringement is difficult to track and enforce.<\/p>\n\n\n\n<p>\u201cThe copyright problem comes with the current generation of imagery tools that are mainly trained on billions of images,\u201d he says. \u201cHowever, this wasn\u2019t an issue a couple of years ago, when artists used to have to use AI through certain models that were trained using the artist\u2019s own images.\u201d<\/p>\n\n\n\n<p>While training models on billions of images taken from the internet might not directly violate copyright law (since the generated images are transformative rather than derivative), it is still considered unethical, Elgammal insists.<\/p>\n\n\n\n<p>AI\u2019s role in misinformation is another major consideration, he says. \u201cHow can we control the data given to an AI?\u201d he asks. \u201cThere are different opinions on everything from politics to religion, lifestyle and everything in between. We can\u2019t censor the data it\u2019s given to support certain voices.\u201d<\/p>\n\n\n\n<p>Elgammal also raises concerns about the environmental impact of AI, noting that just \u201ctraining the API these models use takes a lot of energy.\u201d<\/p>\n\n\n\n<p>Running on Graphics Processing Units (GPUs), known for their high energy consumption, this training can last for days or weeks, iterating over billions of images. This phase forms the bulk of the energy footprint, reflecting a significant demand on power resources. The generation of images, even after training, continues to require substantial energy. Running the models on GPUs to create images adds to the energy consumption, making the entire process from training to generation a power-hungry endeavor.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Lost in Translation<\/h2>\n\n\n\n<p>As generative AI tools become increasingly more sophisticated, the potential for collaboration between humans and artificial intelligence increases exponentially. Elgammal explains how platforms designed for artists to train AI on their own data can lead to new forms of artistic expression, where the machine becomes an extension of the artist\u2019s creativity.<\/p>\n\n\n\n<p>But the newest text-to-image tools, trained on billions of publicly available images, actually <em>decreases<\/em> the level of creativity possible with generative AI, he argues. \u201cWith text prompting, as a way to generate, I think we are losing the fact that AI has been giving us ideas out of the box, or out of [the] ordinary, because now AI is constrained by our language.\u201d<\/p>\n\n\n\n<p>One of the most interesting things about generative AI, says Elgammal, is its ability to visually render our world in novel ways. But text-to-image tools compel AI to look at the world \u201cfrom the lens of our own language,\u201d he explains. \u201cSo we added a constraint that limit[s] the AI\u2019s ability to be imaginative or be engineering interesting concepts visually.\u201d<\/p>\n\n\n\n<p>Language is still useful in other contexts, however, \u201cbecause if you are using AI to generate something, linguistic text or something very structured like music, that\u2019s very important to have language in the process,\u201d he says. \u201cSo we have a long way to go in terms of how AI can fit the creative process for different artists. And what we see now is just still early stages of what is possible.\u201d<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">AI as Creative Assistant<\/h2>\n\n\n\n<p>Artificial intelligence, it turns out, might be best employed as a creative assistant.<\/p>\n\n\n\n<p>Elgammal likens generative AI to a \u201cdigital slave\u201d that can be used to help artists increase their creative output. \u201cFortunately, the AI is not conscious. So having a digital slave in that sense is totally fine,\u201d he says. \u201cThere\u2019s nothing unethical about it.\u201d<\/p>\n\n\n\n<p>He compares the relationship between artist and AI to a director and film crew, or Andy Warhol\u2019s Factory, which had dozens of assistants in varying capacities that allowed Warhol to carry out his creative vision. \u201cBut an emerging artist doesn\u2019t have this ability. So you can use AI to really help you create things at scale.\u201d<\/p>\n\n\n\n<p>An article in the <em>Harvard Business Review<\/em> by <a href=\"https:\/\/hbr.org\/2023\/04\/how-generative-ai-could-disrupt-creative-work\" target=\"_blank\" rel=\"noreferrer noopener\">David De Cremer, Nicola Morini Bianzino, and Ben Falk<\/a> explores this idea further in one of three different \u2014 but not necessarily mutually exclusive \u2014 possible futures they foresee with the use of generative AI.<\/p>\n\n\n\n<p>In this scenario, AI augments human creativity, facilitating faster innovation and enabling rapid iteration, but the human element remains essential.<\/p>\n\n\n\n<p>\u201cToday, most businesses recognize the importance of adopting AI to promote the efficiency and performance of its human workforce,\u201d they write, citing applications such as health care, inventory and logistics, and customer service.<\/p>\n\n\n\n<p>\u201cWith the arrival of generative AI, we\u2019re seeing experiments with augmentation in more creative work,\u201d they continue. \u201cNot quite two years ago, Github introduced Github Copilot, an AI \u2018pair programmer\u2019 that aids the human writing code. More recently, designers, filmmakers, and advertising execs have started using image generators such as DALL-E 2. These tools don\u2019t require users to be very tech savvy. In fact, most of these applications are so easy to use that even children with elementary-level verbal skills can use them to create content right now. Pretty much everyone can make use of them.\u201d<\/p>\n\n\n\n<p>The value proposition this represents is enormous. \u201cThe ability to quickly retrieve, contextualize, and easily interpret knowledge may be the most powerful business application of large-language models,\u201d the authors note. \u201cA natural language interface combined with a powerful AI algorithm will help humans in coming up more quickly with a larger number of ideas and solutions that they subsequently can experiment with to eventually reveal more and better creative output.\u201d<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The Future of Generative AI<\/h2>\n\n\n\n<p>De Cremer, Bianzino and Falk outline two other possible scenarios for the future of generative AI: one where machines monopolize creativity, and another where \u201chuman-made\u201d commands a premium. Again, these aren\u2019t mutually exclusive; any or all of them could occur \u2014 and be occurring \u2014 at the same time.<\/p>\n\n\n\n<p>What the writers call a nascent version of this first scenario could already be in play, they caution. \u201cFor example, recent lawsuits against prominent generative AI platforms allege copyright infringement on a massive scale.\u201d<\/p>\n\n\n\n<p>Making the issue even more fraught is the gap between technological progress and current intellectual property laws. \u201cIt\u2019s quite possible that governments will spend decades fighting over how to balance incentives for technical innovation while retaining incentives for authentic human creation \u2014 a route that would be a terrific loss for human creativity.<\/p>\n\n\n\n<p>\u201cIn this scenario, generative AI significantly changes the incentive structure for creators, and raises risks for businesses and society. If cheaply made generative AI undercuts authentic human content, there\u2019s a real risk that innovation will slow down over time as humans make less and less new art and content.\u201d<\/p>\n\n\n\n<p>The resulting backlash could put even more of a premium on \u201chuman-made,\u201d they argue. \u201cOne plausible effect of being inundated with synthetic creative outputs is that people will begin to value authentic creativity more again and may be willing to pay a premium for it.\u201d<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">READ MORE: <a href=\"https:\/\/hbr.org\/2023\/04\/how-generative-ai-could-disrupt-creative-work\" target=\"_blank\" rel=\"noreferrer noopener\">How Generative AI Could Disrupt Creative Work (Harvard Business Review)<\/a><\/h3>\n\n\n\n<p>Businesses that find success using generative AI tools \u201cwill be the ones that also harness human-centric capabilities such as creativity, curiosity, and compassion,\u201d according to MIT Sloan senior lecturer Paul McDonagh-Smith.<\/p>\n\n\n\n<p>The essential challenge, he said during a recent <a href=\"https:\/\/youtu.be\/MRxQOOxWYA8\" target=\"_blank\" rel=\"noreferrer noopener\">webinar hosted by MIT Sloan Executive Education<\/a>, lies in determining how humans and machines can collaborate most effectively, so that machines\u2019 capabilities enhance and multiply human abilities, rather than diminish or divide them.<\/p>\n\n\n\n<p>It\u2019s up to humans to add the \u201ccreativity quotient\u201d to use technologies like generative AI to their full potential. For organizations, this means creating processes, practices, and policies that empower people to be creative to maximize the power of transformative technologies.<\/p>\n\n\n\n<p>\u201cBoosting your creativity quotient will optimize the use of large language models and generative AI,\u201d he said. \u201cIt will also put all of us in a much better place in terms of how we interface with AI and technology in general.\u201d<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">READ MORE: <a href=\"https:\/\/mitsloan.mit.edu\/ideas-made-to-matter\/why-generative-ai-needs-a-creative-human-touch\" target=\"_blank\" rel=\"noreferrer noopener\">Why generative AI needs a creative human touch (MIT Sloan)<\/a><\/h3>\n\n\n\n<p><a href=\"https:\/\/luttig.substack.com\/p\/hallucinations-in-ai\" target=\"_blank\" rel=\"noreferrer noopener\">Founders Fund principal Jon Luttig<\/a> sees three distinct patterns of behavior in regards to the rapid rise of generative AI: hope, cope, and mope.<\/p>\n\n\n\n<p>\u201cWith a sudden phase change driven by very few people, many technologists fear that the new world we\u2019re entering will leave them behind,\u201d he writes on Substack. \u201cThis fear creates hallucinations including <em>hope<\/em> (the LLM market deployment phase will unfold in a way that benefits me), <em>cope<\/em> (my market position isn\u2019t so bad), and <em>mope<\/em> (the game is already over, and I lost).\u201d<\/p>\n\n\n\n<p>These hallucinations, as the venture capitalist dubs them, \u201cpropel hyperbolic narratives around foundation model FUD [Fear, Uncertainty and Doubt], open source outperformance, incumbent invincibility, investor infatuation, and doomer declarations. It\u2019s hard to know what to believe and who to trust.\u201d<\/p>\n\n\n\n<p>Luttig seeks to dispel these myths, contending that there\u2019s still plenty of room for AI startups to flourish alongside players like Microsoft and Google. The people who want to slow AI down, he argues, are just the copers and mopers who fear that they\u2019re on the wrong end of the equation.<\/p>\n\n\n\n<p>Tell that to the writers and actors out on the picket lines.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">READ MORE: <a href=\"https:\/\/luttig.substack.com\/p\/hallucinations-in-ai\" target=\"_blank\" rel=\"noreferrer noopener\">Hallucinations in AI (John Luttig)<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Thrown into sharp relief by the Hollywood strikes, the debate over human creativity versus generative AI has become a battleground.<\/p>\n","protected":false},"author":2,"featured_media":168371,"menu_order":0,"template":"","meta":{"_acf_changed":false,"_breakdance_hide_in_design_set":false,"_breakdance_tags":""},"categories":[248],"class_list":["post-142469","articles","type-articles","status-publish","has-post-thumbnail","hentry","category-amplify"],"acf":[],"yoast_head":"<!-- This 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